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Study and optimization of the memory management in Memcached
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Over the years the Internet has become more popular than ever and web applications
like Facebook and Twitter are gaining more users. This results in generation of more and
more data by the users which has to be efficiently managed, because access speed is an
important factor nowadays, a user will not wait no more than three seconds for a web
page to load before abandoning the site. In-memory key-value stores like Memcached
and Redis are used to speed up web applications by speeding up access to the data by
decreasing the number of accesses to the slower data storage’s. The first implementation
of Memcached, in the LiveJournal’s website, showed that by using 28 instances of Memcached
on ten unique hosts, caching the most popular 30GB of data can achieve a hit rate
around 92%, reducing the number of accesses to the database and reducing the response
time considerably.
Not all objects in cache take the same time to recompute, so this research is going to
study and present a new cost aware memory management that is easy to integrate in a
key-value store, with this approach being implemented in Memcached. The new memory
management and cache will give some priority to key-value pairs that take longer to be
recomputed. Instead of replacing Memcached’s replacement structure and its policy, we
simply add a new segment in each structure that is capable of storing the more costly
key-value pairs. Apart from this new segment in each replacement structure, we created
a new dynamic cost-aware rebalancing policy in Memcached, giving more memory to
store more costly key-value pairs.
With the implementations of our approaches, we were able to offer a prototype that
can be used to research the cost on the caching systems performance. In addition, we
were able to improve in certain scenarios the access latency of the user and the total
recomputation cost of the key-value stored in the system.
Descrição
Palavras-chave
Web cache Memory management Memcached key-value stores